论文综述想法小计

Posted 2021-02-16 keep-s

大脑肿瘤图像分割：

1. 通过正常大脑的先验模型，对比查找异常值检测，找出非正常区域
2. 假设大脑都是对称的，查找大脑的不对称部分，画出异常区域，感觉这个误差蛮大的。

•  M. Prastawa, E. Bullitt, S. Ho, and G. Gerig, “A brain tumor segmentation framework based on outlier detection,” MedicalImageAnalysis,vol.8,no.3,pp.275–283,2004.
•  M. B. Cuadra, C. Pollo, A. Bardera, O. Cuisenaire, J.-G. Villemure,andJ.-P.Thiran,“Atlas-basedsegmentationof pathological MR brain images using a model of lesion growth,”IEEE Transactions on Medical Imaging,vol.23, no. 10, pp. 1301–1314, 2004.
•  E. I. Zacharaki, D. Shen, S.-K. Lee, and C. Davatzikos, “ORBIT: A multiresolution framework for deformable registration of brain tumor images,” IEEE Transactions on Medical Imaging, vol. 27,no. 8, pp. 1003–1017, 2008.
•  B. H. Menze, K. van Leemput, D. Lashkari, M.-A. Weber, N. Ayache, and P. Golland, “A generative model for brain tumor segmentation in multi-modal images,” in Proc. of MICCAI, pp. 151–159, Springer, 2010. 

　　　3. 基于传统机器学习进行分割（看几篇传统方法的论文）

•  A. Islam, S. M. S. Reza, and K. M. Iftekharuddin, “Multifractal texture estimation for detection and segmentation of brain tumors,” IEEE Transactions on Biomedical Engineering, vol. 60, no. 11, pp. 3204–3215, 2013.
•  N. K. Subbanna, D. Precup, D. L. Collins, and T. Arbel, “Hierarchical probabilistic Gabor and MRF segmentation of brain tumours in MRI volumes,” in Proc. of International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 751–758, Springer, 2013.
•  W. Wu, A. Y. C. Chen, L. Zhao, and J. J. Corso, “Brain tumor detection and segmentation in a CRF (conditional random ?elds) framework with pixel-pairwise af?nity and superpixel-level features,” International Journal of Computer Assisted Radiology and Surgery, vol. 9, no. 2,pp. 241–253, 2014.
•  M. Soltaninejad, G. Yang, T. Lambrou, N. Allinson, T. L. Jones, T. R. Barrick, F. A. Howe, and X. Ye, “Automated brain tumour detection and segmentation using superpixel-based extremely randomized trees in FLAIR MRI,” International Journal of Computer Assisted Radiology and Surgery, vol. 12, no. 2, pp. 183– 203, 2017.
•  D. Zikic, B. Glocker, E. Konukoglu, A. Criminisi, C. Demiralp, J. Shotton, O. M. Thomas, T. Das, R. Jena, and S. J. Price, “Decision forests for tissue-speci?c segmentation of high-grade gliomas in multi-channel MR,” in Proc. of MICCAI, pp. 369–376, Springer, 2012.